{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 利用Python对链家网北京主城区二手房进行数据分析\n",
    "* 本文主要讲述如何通过pandas对爬虫下来的链家数据进行相应的二手房数据分析，主要分析内容包括各个行政区，各个小区的房源信息情况。\n",
    "* 数据来源 https://github.com/XuefengHuang/lianjia-scrawler 该repo提供了python程序进行链家网爬虫，并从中提取二手房价格、面积、户型和二手房关注度等数据。\n",
    "* 分析方法参考 http://www.jianshu.com/p/44f261a62c0f"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入链家网二手房在售房源的文件（数据更新时间2017-11-29）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "import sys\n",
    "\n",
    "stdout = sys.stdout\n",
    "reload(sys)\n",
    "sys.setdefaultencoding('utf-8')\n",
    "sys.stdout = stdout\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']    \n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "#所有在售房源信息\n",
    "house=pd.read_csv('houseinfo.csv')\n",
    "\n",
    "# 所有小区信息\n",
    "community=pd.read_csv('community.csv')\n",
    "\n",
    "# 合并小区信息和房源信息表，可以获得房源更详细的地理位置\n",
    "community['community'] = community['title']\n",
    "house_detail = pd.merge(house, community, on='community')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将数据从字符串提取出来"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将字符串转换成数字\n",
    "def data_adj(area_data, str):       \n",
    "    if str in area_data :        \n",
    "        return float(area_data[0 : area_data.find(str)])    \n",
    "    else :        \n",
    "        return None\n",
    "# 处理房屋面积数据\n",
    "house['square'] = house['square'].apply(data_adj,str = '平米')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 删除车位信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "记录中共有车位32个\n",
      "现在还剩下16076条记录\n"
     ]
    }
   ],
   "source": [
    "car=house[house.housetype.str.contains('车位')]\n",
    "print '记录中共有车位%d个'%car.shape[0]\n",
    "house.drop(car.index,inplace=True)\n",
    "print '现在还剩下%d条记录'%house.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 价格最高的5个别墅"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "记录中共有别墅50栋\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>houseID</th>\n",
       "      <th>title</th>\n",
       "      <th>link</th>\n",
       "      <th>community</th>\n",
       "      <th>years</th>\n",
       "      <th>housetype</th>\n",
       "      <th>square</th>\n",
       "      <th>direction</th>\n",
       "      <th>floor</th>\n",
       "      <th>taxtype</th>\n",
       "      <th>totalPrice</th>\n",
       "      <th>unitPrice</th>\n",
       "      <th>followInfo</th>\n",
       "      <th>validdate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8020</th>\n",
       "      <td>101102078117</td>\n",
       "      <td>香山清琴二期独栋别墅，毛坯房原始户型，花园1200平米</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101102078117...</td>\n",
       "      <td>香山清琴</td>\n",
       "      <td>2层2007年建</td>\n",
       "      <td>独栋别墅</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1002.56平米</td>\n",
       "      <td>2层2007年建</td>\n",
       "      <td>房本满五年</td>\n",
       "      <td>12500</td>\n",
       "      <td>124681</td>\n",
       "      <td>45人关注 / 共7次带看 / 2个月以前发布</td>\n",
       "      <td>2017-11-29 14:31:35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>101100652295</td>\n",
       "      <td>千尺独栋 北入户 红顶商人金融界入住社区</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101100652295...</td>\n",
       "      <td>龙湖颐和原著</td>\n",
       "      <td>2层2010年建</td>\n",
       "      <td>独栋别墅</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1071.32平米</td>\n",
       "      <td>2层2010年建</td>\n",
       "      <td>距离4号线西苑站839米房本满五年</td>\n",
       "      <td>12000</td>\n",
       "      <td>112012</td>\n",
       "      <td>231人关注 / 共26次带看 / 一年前发布</td>\n",
       "      <td>2017-11-29 14:36:53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2729</th>\n",
       "      <td>101101641953</td>\n",
       "      <td>临湖独栋别墅 花园半亩 观景湖面和绿化 满五年有车库房主自荐</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101641953...</td>\n",
       "      <td>紫玉山庄</td>\n",
       "      <td>3层2000年建</td>\n",
       "      <td>独栋别墅</td>\n",
       "      <td>NaN</td>\n",
       "      <td>403.72平米</td>\n",
       "      <td>3层2000年建</td>\n",
       "      <td>房本满五年</td>\n",
       "      <td>6000</td>\n",
       "      <td>148618</td>\n",
       "      <td>108人关注 / 共16次带看 / 5个月以前发布</td>\n",
       "      <td>2017-11-28 16:42:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3141</th>\n",
       "      <td>101101684273</td>\n",
       "      <td>银湖别墅 独栋 望京公园旁 五环里 封闭式社区</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101684273...</td>\n",
       "      <td>银湖别墅</td>\n",
       "      <td>3层1998年建</td>\n",
       "      <td>独栋别墅</td>\n",
       "      <td>NaN</td>\n",
       "      <td>383.59平米</td>\n",
       "      <td>3层1998年建</td>\n",
       "      <td>房本满五年</td>\n",
       "      <td>5000</td>\n",
       "      <td>130348</td>\n",
       "      <td>9人关注 / 共3次带看 / 5个月以前发布</td>\n",
       "      <td>2017-11-28 15:20:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4112</th>\n",
       "      <td>101101796191</td>\n",
       "      <td>首排别墅 位置好 全景小区绿化和人工湖 有车库</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101796191...</td>\n",
       "      <td>亚运新新家园朗月园一期</td>\n",
       "      <td>1层2003年建</td>\n",
       "      <td>联排别墅</td>\n",
       "      <td>NaN</td>\n",
       "      <td>461.37平米</td>\n",
       "      <td>1层2003年建</td>\n",
       "      <td>房本满五年</td>\n",
       "      <td>3800</td>\n",
       "      <td>82364</td>\n",
       "      <td>0人关注 / 共4次带看 / 4个月以前发布</td>\n",
       "      <td>2017-11-28 15:34:28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           houseID                           title  \\\n",
       "8020  101102078117     香山清琴二期独栋别墅，毛坯房原始户型，花园1200平米   \n",
       "102   101100652295            千尺独栋 北入户 红顶商人金融界入住社区   \n",
       "2729  101101641953  临湖独栋别墅 花园半亩 观景湖面和绿化 满五年有车库房主自荐   \n",
       "3141  101101684273         银湖别墅 独栋 望京公园旁 五环里 封闭式社区   \n",
       "4112  101101796191         首排别墅 位置好 全景小区绿化和人工湖 有车库   \n",
       "\n",
       "                                                   link    community  \\\n",
       "8020  https://bj.lianjia.com/ershoufang/101102078117...         香山清琴   \n",
       "102   https://bj.lianjia.com/ershoufang/101100652295...       龙湖颐和原著   \n",
       "2729  https://bj.lianjia.com/ershoufang/101101641953...         紫玉山庄   \n",
       "3141  https://bj.lianjia.com/ershoufang/101101684273...         银湖别墅   \n",
       "4112  https://bj.lianjia.com/ershoufang/101101796191...  亚运新新家园朗月园一期   \n",
       "\n",
       "         years housetype  square  direction     floor            taxtype  \\\n",
       "8020  2层2007年建      独栋别墅     NaN  1002.56平米  2层2007年建              房本满五年   \n",
       "102   2层2010年建      独栋别墅     NaN  1071.32平米  2层2010年建  距离4号线西苑站839米房本满五年   \n",
       "2729  3层2000年建      独栋别墅     NaN   403.72平米  3层2000年建              房本满五年   \n",
       "3141  3层1998年建      独栋别墅     NaN   383.59平米  3层1998年建              房本满五年   \n",
       "4112  1层2003年建      联排别墅     NaN   461.37平米  1层2003年建              房本满五年   \n",
       "\n",
       "      totalPrice  unitPrice                 followInfo            validdate  \n",
       "8020       12500     124681    45人关注 / 共7次带看 / 2个月以前发布  2017-11-29 14:31:35  \n",
       "102        12000     112012    231人关注 / 共26次带看 / 一年前发布  2017-11-29 14:36:53  \n",
       "2729        6000     148618  108人关注 / 共16次带看 / 5个月以前发布  2017-11-28 16:42:18  \n",
       "3141        5000     130348     9人关注 / 共3次带看 / 5个月以前发布  2017-11-28 15:20:06  \n",
       "4112        3800      82364     0人关注 / 共4次带看 / 4个月以前发布  2017-11-28 15:34:28  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bieshu=house[house.housetype.str.contains('别墅')]\n",
    "print '记录中共有别墅%d栋'%bieshu.shape[0]\n",
    "bieshu.sort_values('totalPrice',ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 删除别墅信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "现在还剩下16026条记录\n"
     ]
    }
   ],
   "source": [
    "house.drop(bieshu.index,inplace=True)\n",
    "print '现在还剩下%d条记录'%house.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 获取总价前五的房源信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>houseID</th>\n",
       "      <th>title</th>\n",
       "      <th>link</th>\n",
       "      <th>community</th>\n",
       "      <th>years</th>\n",
       "      <th>housetype</th>\n",
       "      <th>square</th>\n",
       "      <th>direction</th>\n",
       "      <th>floor</th>\n",
       "      <th>taxtype</th>\n",
       "      <th>totalPrice</th>\n",
       "      <th>unitPrice</th>\n",
       "      <th>followInfo</th>\n",
       "      <th>validdate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8571</th>\n",
       "      <td>101102105035</td>\n",
       "      <td>中关村创业大街对过 有名的公司入驻其中正规写字楼</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101102105035...</td>\n",
       "      <td>银科大厦</td>\n",
       "      <td>低楼层(共22层)2004年建塔楼</td>\n",
       "      <td>1房间0卫</td>\n",
       "      <td>2623.28</td>\n",
       "      <td>东 南 西 北</td>\n",
       "      <td>低楼层(共22层)2004年建塔楼</td>\n",
       "      <td>距离10号线苏州街站898米房本满五年</td>\n",
       "      <td>12000</td>\n",
       "      <td>45745</td>\n",
       "      <td>1人关注 / 共0次带看 / 2个月以前发布</td>\n",
       "      <td>2017-11-29 14:07:32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11758</th>\n",
       "      <td>101102235883</td>\n",
       "      <td>中关村创业大街对过 有名的公司入驻其中正规一层底商</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101102235883...</td>\n",
       "      <td>银科大厦</td>\n",
       "      <td>底层(共22层)2004年建塔楼</td>\n",
       "      <td>1房间0卫</td>\n",
       "      <td>1182.80</td>\n",
       "      <td>东北</td>\n",
       "      <td>底层(共22层)2004年建塔楼</td>\n",
       "      <td>距离10号线苏州街站898米房本满五年</td>\n",
       "      <td>12000</td>\n",
       "      <td>101455</td>\n",
       "      <td>0人关注 / 共0次带看 / 1个月以前发布</td>\n",
       "      <td>2017-11-29 14:07:33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2480</th>\n",
       "      <td>101101608106</td>\n",
       "      <td>西山别墅区拥有900平大花园纯独栋社区房主自荐</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101608106...</td>\n",
       "      <td>香山清琴</td>\n",
       "      <td>1层2007年建</td>\n",
       "      <td>7室3厅</td>\n",
       "      <td>482.16</td>\n",
       "      <td>南 北</td>\n",
       "      <td>1层2007年建</td>\n",
       "      <td>房本满五年</td>\n",
       "      <td>7000</td>\n",
       "      <td>145181</td>\n",
       "      <td>94人关注 / 共24次带看 / 6个月以前发布</td>\n",
       "      <td>2017-11-29 14:31:34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14492</th>\n",
       "      <td>101102306092</td>\n",
       "      <td>盘古大观 大平层 观景房 格局可塑性强！</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101102306092...</td>\n",
       "      <td>盘古大观</td>\n",
       "      <td>中楼层(共22层)2007年建塔楼</td>\n",
       "      <td>3室2厅</td>\n",
       "      <td>671.35</td>\n",
       "      <td>东 南 西</td>\n",
       "      <td>中楼层(共22层)2007年建塔楼</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6700</td>\n",
       "      <td>99799</td>\n",
       "      <td>16人关注 / 共0次带看 / 13天以前发布</td>\n",
       "      <td>2017-11-28 15:19:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10154</th>\n",
       "      <td>101102178295</td>\n",
       "      <td>朝阳公园内建筑，视野好，可以俯视朝阳公园美景</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101102178295...</td>\n",
       "      <td>霄云路8号</td>\n",
       "      <td>高楼层(共27层)2011年建塔楼</td>\n",
       "      <td>4室3厅</td>\n",
       "      <td>453.64</td>\n",
       "      <td>南 北</td>\n",
       "      <td>高楼层(共27层)2011年建塔楼</td>\n",
       "      <td>房本满两年</td>\n",
       "      <td>5500</td>\n",
       "      <td>121242</td>\n",
       "      <td>39人关注 / 共4次带看 / 1个月以前发布</td>\n",
       "      <td>2017-11-28 15:52:12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            houseID                      title  \\\n",
       "8571   101102105035   中关村创业大街对过 有名的公司入驻其中正规写字楼   \n",
       "11758  101102235883  中关村创业大街对过 有名的公司入驻其中正规一层底商   \n",
       "2480   101101608106    西山别墅区拥有900平大花园纯独栋社区房主自荐   \n",
       "14492  101102306092       盘古大观 大平层 观景房 格局可塑性强！   \n",
       "10154  101102178295     朝阳公园内建筑，视野好，可以俯视朝阳公园美景   \n",
       "\n",
       "                                                    link community  \\\n",
       "8571   https://bj.lianjia.com/ershoufang/101102105035...      银科大厦   \n",
       "11758  https://bj.lianjia.com/ershoufang/101102235883...      银科大厦   \n",
       "2480   https://bj.lianjia.com/ershoufang/101101608106...      香山清琴   \n",
       "14492  https://bj.lianjia.com/ershoufang/101102306092...      盘古大观   \n",
       "10154  https://bj.lianjia.com/ershoufang/101102178295...     霄云路8号   \n",
       "\n",
       "                   years housetype   square direction              floor  \\\n",
       "8571   低楼层(共22层)2004年建塔楼     1房间0卫  2623.28   东 南 西 北  低楼层(共22层)2004年建塔楼   \n",
       "11758   底层(共22层)2004年建塔楼     1房间0卫  1182.80        东北   底层(共22层)2004年建塔楼   \n",
       "2480            1层2007年建      7室3厅   482.16       南 北           1层2007年建   \n",
       "14492  中楼层(共22层)2007年建塔楼      3室2厅   671.35     东 南 西  中楼层(共22层)2007年建塔楼   \n",
       "10154  高楼层(共27层)2011年建塔楼      4室3厅   453.64       南 北  高楼层(共27层)2011年建塔楼   \n",
       "\n",
       "                   taxtype  totalPrice  unitPrice                followInfo  \\\n",
       "8571   距离10号线苏州街站898米房本满五年       12000      45745    1人关注 / 共0次带看 / 2个月以前发布   \n",
       "11758  距离10号线苏州街站898米房本满五年       12000     101455    0人关注 / 共0次带看 / 1个月以前发布   \n",
       "2480                 房本满五年        7000     145181  94人关注 / 共24次带看 / 6个月以前发布   \n",
       "14492                  NaN        6700      99799   16人关注 / 共0次带看 / 13天以前发布   \n",
       "10154                房本满两年        5500     121242   39人关注 / 共4次带看 / 1个月以前发布   \n",
       "\n",
       "                 validdate  \n",
       "8571   2017-11-29 14:07:32  \n",
       "11758  2017-11-29 14:07:33  \n",
       "2480   2017-11-29 14:31:34  \n",
       "14492  2017-11-28 15:19:41  \n",
       "10154  2017-11-28 15:52:12  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house.sort_values('totalPrice',ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 获取户型数量分布信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ee3f3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housetype = house['housetype'].value_counts()\n",
    "housetype.head(8).plot(kind='bar',x='housetype',y='size', title='户型数量分布')\n",
    "plt.legend(['数量']) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 关注人数最多5套房子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>houseID</th>\n",
       "      <th>title</th>\n",
       "      <th>link</th>\n",
       "      <th>community</th>\n",
       "      <th>years</th>\n",
       "      <th>housetype</th>\n",
       "      <th>square</th>\n",
       "      <th>direction</th>\n",
       "      <th>floor</th>\n",
       "      <th>taxtype</th>\n",
       "      <th>totalPrice</th>\n",
       "      <th>unitPrice</th>\n",
       "      <th>followInfo</th>\n",
       "      <th>validdate</th>\n",
       "      <th>guanzhu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>101100379913</td>\n",
       "      <td>弘善家园南向开间，满两年，免增值税</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101100379913...</td>\n",
       "      <td>弘善家园</td>\n",
       "      <td>中楼层(共28层)2009年建塔楼</td>\n",
       "      <td>1室0厅</td>\n",
       "      <td>42.64</td>\n",
       "      <td>南</td>\n",
       "      <td>中楼层(共28层)2009年建塔楼</td>\n",
       "      <td>距离10号线十里河站698米房本满两年随时看房</td>\n",
       "      <td>265</td>\n",
       "      <td>62149</td>\n",
       "      <td>1401人关注 / 共305次带看 / 一年前发布</td>\n",
       "      <td>2017-11-29 09:34:23</td>\n",
       "      <td>1401.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2313</th>\n",
       "      <td>101101588951</td>\n",
       "      <td>四惠东 康家园 南向一居室 地铁1号线出行房主自荐</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101588951...</td>\n",
       "      <td>康家园</td>\n",
       "      <td>顶层(共6层)1995年建板楼</td>\n",
       "      <td>1室1厅</td>\n",
       "      <td>41.97</td>\n",
       "      <td>南</td>\n",
       "      <td>顶层(共6层)1995年建板楼</td>\n",
       "      <td>距离1号线四惠东站974米房本满五年随时看房</td>\n",
       "      <td>262</td>\n",
       "      <td>62426</td>\n",
       "      <td>1005人关注 / 共86次带看 / 6个月以前发布</td>\n",
       "      <td>2017-11-28 17:21:58</td>\n",
       "      <td>1005.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>101101355617</td>\n",
       "      <td>远见名苑  东南两居  满五年家庭唯一住房 诚心出售房主自荐</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101355617...</td>\n",
       "      <td>远见名苑</td>\n",
       "      <td>中楼层(共24层)2004年建塔楼</td>\n",
       "      <td>2室1厅</td>\n",
       "      <td>90.14</td>\n",
       "      <td>东南</td>\n",
       "      <td>中楼层(共24层)2004年建塔楼</td>\n",
       "      <td>距离7号线达官营站516米房本满五年</td>\n",
       "      <td>811</td>\n",
       "      <td>89972</td>\n",
       "      <td>979人关注 / 共50次带看 / 8个月以前发布</td>\n",
       "      <td>2017-11-29 10:09:39</td>\n",
       "      <td>979.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2331</th>\n",
       "      <td>101101590746</td>\n",
       "      <td>荣丰二期朝南复式无遮挡全天采光房主自荐</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101590746...</td>\n",
       "      <td>荣丰2008</td>\n",
       "      <td>中楼层(共10层)2005年建塔楼</td>\n",
       "      <td>1室1厅</td>\n",
       "      <td>32.54</td>\n",
       "      <td>南</td>\n",
       "      <td>中楼层(共10层)2005年建塔楼</td>\n",
       "      <td>距离7号线达官营站1028米房本满五年随时看房</td>\n",
       "      <td>400</td>\n",
       "      <td>122926</td>\n",
       "      <td>972人关注 / 共369次带看 / 6个月以前发布</td>\n",
       "      <td>2017-11-29 10:08:38</td>\n",
       "      <td>972.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>915</th>\n",
       "      <td>101101327417</td>\n",
       "      <td>通州万达北苑地铁站 天时名苑 大两居可改3居</td>\n",
       "      <td>https://bj.lianjia.com/ershoufang/101101327417...</td>\n",
       "      <td>天时名苑</td>\n",
       "      <td>顶层(共9层)2009年建板塔结合</td>\n",
       "      <td>2室2厅</td>\n",
       "      <td>121.30</td>\n",
       "      <td>南 北</td>\n",
       "      <td>顶层(共9层)2009年建板塔结合</td>\n",
       "      <td>距离八通线通州北苑站602米房本满五年</td>\n",
       "      <td>645</td>\n",
       "      <td>53174</td>\n",
       "      <td>894人关注 / 共228次带看 / 8个月以前发布</td>\n",
       "      <td>2017-11-29 09:20:13</td>\n",
       "      <td>894.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           houseID                           title  \\\n",
       "47    101100379913               弘善家园南向开间，满两年，免增值税   \n",
       "2313  101101588951       四惠东 康家园 南向一居室 地铁1号线出行房主自荐   \n",
       "990   101101355617  远见名苑  东南两居  满五年家庭唯一住房 诚心出售房主自荐   \n",
       "2331  101101590746             荣丰二期朝南复式无遮挡全天采光房主自荐   \n",
       "915   101101327417          通州万达北苑地铁站 天时名苑 大两居可改3居   \n",
       "\n",
       "                                                   link community  \\\n",
       "47    https://bj.lianjia.com/ershoufang/101100379913...      弘善家园   \n",
       "2313  https://bj.lianjia.com/ershoufang/101101588951...       康家园   \n",
       "990   https://bj.lianjia.com/ershoufang/101101355617...      远见名苑   \n",
       "2331  https://bj.lianjia.com/ershoufang/101101590746...    荣丰2008   \n",
       "915   https://bj.lianjia.com/ershoufang/101101327417...      天时名苑   \n",
       "\n",
       "                  years housetype  square direction              floor  \\\n",
       "47    中楼层(共28层)2009年建塔楼      1室0厅   42.64         南  中楼层(共28层)2009年建塔楼   \n",
       "2313    顶层(共6层)1995年建板楼      1室1厅   41.97         南    顶层(共6层)1995年建板楼   \n",
       "990   中楼层(共24层)2004年建塔楼      2室1厅   90.14        东南  中楼层(共24层)2004年建塔楼   \n",
       "2331  中楼层(共10层)2005年建塔楼      1室1厅   32.54         南  中楼层(共10层)2005年建塔楼   \n",
       "915   顶层(共9层)2009年建板塔结合      2室2厅  121.30       南 北  顶层(共9层)2009年建板塔结合   \n",
       "\n",
       "                      taxtype  totalPrice  unitPrice  \\\n",
       "47    距离10号线十里河站698米房本满两年随时看房         265      62149   \n",
       "2313   距离1号线四惠东站974米房本满五年随时看房         262      62426   \n",
       "990        距离7号线达官营站516米房本满五年         811      89972   \n",
       "2331  距离7号线达官营站1028米房本满五年随时看房         400     122926   \n",
       "915       距离八通线通州北苑站602米房本满五年         645      53174   \n",
       "\n",
       "                      followInfo            validdate  guanzhu  \n",
       "47     1401人关注 / 共305次带看 / 一年前发布  2017-11-29 09:34:23   1401.0  \n",
       "2313  1005人关注 / 共86次带看 / 6个月以前发布  2017-11-28 17:21:58   1005.0  \n",
       "990    979人关注 / 共50次带看 / 8个月以前发布  2017-11-29 10:09:39    979.0  \n",
       "2331  972人关注 / 共369次带看 / 6个月以前发布  2017-11-29 10:08:38    972.0  \n",
       "915   894人关注 / 共228次带看 / 8个月以前发布  2017-11-29 09:20:13    894.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house['guanzhu'] = house['followInfo'].apply(data_adj,str = '人关注')\n",
    "house.sort_values('guanzhu',ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 户型和关注人数分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QEZHyqFSngTpgAvB9d88VRNsHuBJ4DdiUUGQNQnnpJ939uzFB5OyVbOGYWatj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\nSjgiIlIV/x+cdVP0/GJS0gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1078ddc10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(1,1)    \n",
    "type_interest_group = house['guanzhu'].groupby(house['housetype']).agg([('户型', 'count'), ('关注人数', 'sum')])    \n",
    "#取户型>50的数据进行可视化\n",
    "ti_sort = type_interest_group[type_interest_group['户型'] > 50].sort_values(by='户型')    \n",
    "ti_sort.plot(kind='barh', alpha=0.7, grid=True, ax=ax1)    \n",
    "plt.title('二手房户型和关注人数分布')    \n",
    "plt.ylabel('户型') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 面积分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sm54F7AK8GhErJM0ERr/his3MrEPKDnzgY8CngLuA+cAfs/mDgJXAuqJ1NwAr2kxvQNJ4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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f199c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax2 = plt.subplots(1,1)    \n",
    "area_level = [0, 50, 100, 150, 200, 250, 300, 500]    \n",
    "label_level = ['小于50', '50-100', '100-150', '150-200', '200-250', '250-300', '300-350']    \n",
    "area_cut = pd.cut(house['square'], area_level, labels=label_level)        \n",
    "area_cut.value_counts().plot(kind='bar', rot=30, alpha=0.4, grid=True, fontsize='small', ax=ax2)    \n",
    "plt.title('二手房面积分布')    \n",
    "plt.xlabel('面积')    \n",
    "plt.legend(['数量'])    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 聚类分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>关注人数</th>\n",
       "      <th>面积</th>\n",
       "      <th>房价</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49.828329</td>\n",
       "      <td>135.012281</td>\n",
       "      <td>1139.387478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48.573579</td>\n",
       "      <td>256.357676</td>\n",
       "      <td>2549.974916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>61.465875</td>\n",
       "      <td>74.495457</td>\n",
       "      <td>515.516434</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        关注人数          面积           房价\n",
       "0  49.828329  135.012281  1139.387478\n",
       "1  48.573579  256.357676  2549.974916\n",
       "2  61.465875   74.495457   515.516434"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 缺失值处理:直接将缺失值去掉    \n",
    "cluster_data = house[['guanzhu','square','totalPrice']].dropna()    \n",
    "#将簇数设为3    \n",
    "K_model = KMeans(n_clusters=3)    \n",
    "alg = K_model.fit(cluster_data)    \n",
    "'------聚类中心------'   \n",
    "center = pd.DataFrame(alg.cluster_centers_, columns=['关注人数','面积','房价'])    \n",
    "cluster_data['label'] = alg.labels_ \n",
    "center"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 北京市在售面积最小二手房"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "houseID                                            101102324602\n",
       "title                                      智德北巷（北河沿大街）+小户型一居+南向\n",
       "link          https://bj.lianjia.com/ershoufang/101102324602...\n",
       "community                                                  智德北巷\n",
       "years                                          中楼层(共6层)1985年建板楼\n",
       "housetype                                                  1室0厅\n",
       "square                                                    15.29\n",
       "direction                                                     南\n",
       "floor                                          中楼层(共6层)1985年建板楼\n",
       "taxtype                                          距离5号线灯市口站1113米\n",
       "totalPrice                                                  220\n",
       "unitPrice                                                143885\n",
       "followInfo                               56人关注 / 共2次带看 / 8天以前发布\n",
       "validdate                                   2017-11-29 13:23:16\n",
       "guanzhu                                                      56\n",
       "Name: 15260, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house.sort_values('square').iloc[0,:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 北京市在售面积最大二手房"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "houseID                                            101102105035\n",
       "title                                  中关村创业大街对过 有名的公司入驻其中正规写字楼\n",
       "link          https://bj.lianjia.com/ershoufang/101102105035...\n",
       "community                                                  银科大厦\n",
       "years                                         低楼层(共22层)2004年建塔楼\n",
       "housetype                                                 1房间0卫\n",
       "square                                                  2623.28\n",
       "direction                                               东 南 西 北\n",
       "floor                                         低楼层(共22层)2004年建塔楼\n",
       "taxtype                                     距离10号线苏州街站898米房本满五年\n",
       "totalPrice                                                12000\n",
       "unitPrice                                                 45745\n",
       "followInfo                               1人关注 / 共0次带看 / 2个月以前发布\n",
       "validdate                                   2017-11-29 14:07:32\n",
       "guanzhu                                                       1\n",
       "Name: 8571, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house.sort_values('square',ascending=False).iloc[0,:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 各个行政区房源均价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1078c1f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "house_unitprice_perdistrict = house_detail.groupby('district').mean()['unitPrice']\n",
    "house_unitprice_perdistrict.plot(kind='bar',x='district',y='unitPrice', title='各个行政区房源均价')\n",
    "plt.legend(['均价']) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 各个区域房源数量排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VjAO7mVnNOLCbmdWMA7uZWc04sJuZ1YwDu5lZzTiwm5nVjAO7mVnNOLCbmdWMA7uZWc04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\nP84vxp3slQ7XAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f199250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bizcircle_count=house_detail.groupby('bizcircle').size().sort_values(ascending=False)\n",
    "bizcircle_count.head(20).plot(kind='bar',x='bizcircle',y='size', title='各个区域房源数量分布')\n",
    "plt.legend(['数量']) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 各个区域均价排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7vR4j9lui6iMREckoKIiISEZBQUREMgoKIiKSUVAQEZGMgoKIiGQUFEREJKOgICIiGQUF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\niGQUFEREJKOgICIimf8P6ioFCE7YAKQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f17cc10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bizcircle_unitprice=house_detail.groupby('bizcircle').mean()['unitPrice'].sort_values(ascending=False)\n",
    "bizcircle_unitprice.head(20).plot(kind='bar',x='bizcircle',y='unitPrice', title='各个区域均价分布')\n",
    "plt.legend(['均价']) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 各个区域小区数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OHdvOy5qZWRNaDuylzv1nwIE1JflpwJbl8YbA9I7kzszMWtbOAKWjgFWB0yUBfIlsXL1C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\nA+QAP65I6TjTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f8158d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bizcircle_community=community.groupby('bizcircle')['title'].size().sort_values(ascending=False)\n",
    "bizcircle_community.head(20).plot(kind='bar', x='bizcircle',y='size', title='各个区域小区数量分布')\n",
    "plt.legend(['数量']) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 按小区均价排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WD+YbFCJiekRM654uaV/g/yLiCbIW8Xh5aDowsmZa92MdLmmSpElTp07t5Z9mZmZ9Vamj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\nmJlZk4OCmZk1OSiYmVmTg4KZmTX9Pxy6gocSK5huAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107761850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "community_unitprice = house.groupby('community').mean()['unitPrice'].sort_values(ascending=False)\n",
    "community_unitprice.head(15).plot(kind='bar',x='community',y='unitPrice', title='各个小区均价分布')\n",
    "plt.legend(['均价']) \n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "test"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
